Frequent mutations of genes encoding ubiquitin-mediated proteolysis pathway components in clear cell renal cell carcinoma

Genomic characterization of AML with aberrations of chromosome 7: a multinational cohort of 519 patients

BACKGROUND

Deletions and partial losses of chromosome 7 (chr7) are frequent in acute myeloid leukemia (AML) and are linked to dismal outcome. However, the genomic landscape and prognostic impact of concomitant genetic aberrations remain incompletely understood.

METHODS

To discover genetic lesions in adult AML patients with aberrations of chromosome 7 [abn(7)], 60 paired diagnostic/remission samples were investigated by whole-exome sequencing in the exploration cohort. Subsequently, a gene panel including 66 genes and a SNP backbone for copy-number variation detection was designed and applied to the remaining samples of the validation cohort. In total, 519 patients were investigated, of which 415 received intensive induction treatment, typically containing a combination of cytarabine and anthracyclines.

RESULTS

In the exploration cohort, the most frequently mutated gene was TP53 (33%), followed by epigenetic regulators (DNMT3A, KMT2C, IDH2) and signaling genes (NRAS, PTPN11). Thirty percent of 519 patients harbored ≥ 1 mutation in genes located in commonly deleted regions of chr7-most frequently affecting KMT2C (16%) and EZH2 (10%). KMT2C mutations were often subclonal and enriched in patients with del(7q), de novo or core-binding factor AML (45%). Cancer cell fraction analysis and reconstruction of mutation acquisition identified TP53 mutations as mainly disease-initiating events, while del(7q) or -7 appeared as subclonal events in one-third of cases. Multivariable analysis identified five genetic lesions with significant prognostic impact in intensively treated AML patients with abn(7). Mutations in TP53 and PTPN11 (11%) showed the strongest association with worse overall survival (OS, TP53: hazard ratio [HR], 2.53 [95% CI 1.66-3.86]; P < 0.001; PTPN11: HR, 2.24 [95% CI 1.56-3.22]; P < 0.001) and relapse-free survival (RFS, TP53: HR, 2.3 [95% CI 1.25-4.26]; P = 0.008; PTPN11: HR, 2.32 [95% CI 1.33-4.04]; P = 0.003). By contrast, IDH2-mutated patients (9%) displayed prolonged OS (HR, 0.51 [95% CI 0.30-0.88]; P = 0.0015) and durable responses (RFS: HR, 0.5 [95% CI 0.26-0.96]; P = 0.036).

CONCLUSION

This work unraveled formerly underestimated genetic lesions and provides a comprehensive overview of the spectrum of recurrent gene mutations and their clinical relevance in AML with abn(7). KMT2C mutations are among the most frequent gene mutations in this heterogeneous AML subgroup and warrant further functional investigation.

Frequent gene mutations and the correlations with clinicopathological features in clear cell renal cell carcinoma: preliminary study based on Chinese population and TCGA database

BACKGROUND

Large-scale sequencing plays important roles in revealing the genomic map of ccRCC and predicting prognosis and therapeutic response to targeted drugs. However, the relevant clinical data is still sparse in Chinese population.

METHODS

Fresh tumor specimens were collected from 66 Chinese ccRCC patients, then the genomic RNAs were subjected to whole transcriptome sequencing (WTS). We comprehensively analyzed the frequently mutated genes from our hospital's cohort as well as TCGA-KIRC cohort.

RESULTS

VHL gene is the most frequently mutated gene in ccRCC. In our cohort, BAP1 and PTEN are significantly associated with a higher tumor grade and DNM2 is significantly associated with a lower tumor grade. The mutant type (MT) groups of BAP1 or PTEN, BAP1 or SETD2, BAP1 or TP53, BAP1 or MTOR, BAP1 or FAT1 and BAP1 or AR had a significantly correlation with higher tumor grade in our cohort. Moreover, we identified HMCN1 was a hub mutant gene which was closely related to worse prognosis and may enhance anti-tumor immune responses.

CONCLUSIONS

In this preliminary research, we comprehensively analyzed the frequently mutated genes in the Chinese population and TCGA database, which may bring new insights to the diagnosis and medical treatment of ccRCC.

Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing for a detailed description of the somatic mutational landscape of ccRCC. We identify candidate driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for therapeutic interventions. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The observations that higher T-cell infiltration is associated with better overall survival and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.

TNFSF9 Is Associated with Favorable Tumor Immune Microenvironment in Patients with Renal Cell Carcinoma Who Are Treated with the Combination Therapy of Nivolumab and Ipilimumab

Combination therapy of nivolumab and ipilimumab (NIVO + IPI) for metastatic renal cell carcinoma (mRCC) has shown efficacy, but approximately 20% of patients experience disease progression in the early stages of treatment. No useful biomarkers have been reported to date. Therefore, it is desirable to identify biomarkers to predict treatment responses in advance. We examined the tumor microenvironment (TME)-related gene expression in mRCC patients treated with NIVO + IPI, between the response and non-response groups, using tumor tissues, before administering NIVO + IPI. In TME-related genes, TNFSF9 expression was identified as a candidate for the predictive biomarker. Its expression discriminated between the response and non-response groups with 88.89% sensitivity and 87.50% specificity (AUC = 0.9444). We further analyzed the roles of TNFSF9 in TME using bioinformatics from The Cancer Genome Atlas (TCGA) cohort. An adaptive immune response was activated in the TNFSF9-high-expression tumors. Indeed, T follicular helper cells, plasma B cells, and tumor-infiltrating CD8+ T cells were increased in the tumors, which indicates the promotion of humoral immunity due to enhanced T-B interactions. However, as the number of regulatory T cells (Treg) increased in the tumors, the percentage of dysfunctional T cells also increased. This suggests that not only PD-1 but also CTLA-4 inhibition may have suppressed Treg activation and improved the therapeutic effect in the TNFSF9 high-expression tumors. Therefore, TNFSF9 may predict the therapeutic efficacy of NIVO + IPI for mRCC and allow more appropriate patient selection.

Effect of irrigation on wild and inbred maize with relation to the antioxidant status of pollens, flag leaves, and developing grains

The investigation was carried out to evaluate the net effect of limited irrigation on the antioxidant status of pollens, flag leaves, and developing grains of wild and inbred maize lines. Teosinte pollens showed the highest activities of superoxide dismutase (SOD), catalase (CAT), glutathione reductase (GR), glutathione-s-transferase (GST), and peroxidase (POX) under stressful conditions while LM 11 showed a significant decrease in APX, CAT, GR, and GST activities. Limited irrigations increased the contents of superoxide and malondialdehyde (MDA) to maximum levels in LM 11 leaves. The pollens, leaves, and developing grains of teosinte had the highest content of total phenols. Proline was maximum in the developing grains of teosinte and CML 32 while lowest in those of LM 11. Principal component analysis showed that LM 11 genotype and the respective antioxidant enzymes were in completely opposite quadrants. Chord analysis showed that CAT activity and total phenol content in pollens, leaves, and developing grains contributed towards most of the variations observed in teosinte and might be responsible for managing the yield attributes of genotype during stress conditions. The pollens and leaves of teosinte, with significant SOD activity, further helped in optimizing plant yield, under stressful conditions. CML 32 occupied intermediate position owing to the unaffected activities of most of the antioxidant enzymes and high content of antioxidants in its tissues. It may be concluded that the overall antioxidant status of tissues decides the tolerance behavior of plants.

Development of prognostic signatures and risk index related to lipid metabolism in ccRCC

Background

Clear cell renal cell carcinoma (ccRCC) is a metabolic disorder characterized by abnormal lipid accumulation in the cytoplasm. Lipid metabolism-related genes may have important clinical significance for prognosis prediction and individualized treatment.

Methods

We collected bulk and single-cell transcriptomic data of ccRCC and normal samples to identify key lipid metabolism-related prognostic signatures. qPCR was used to confirm the expression of signatures in cancer cell lines. Based on the identified signatures, we developed a lipid metabolism risk score (LMRS) as a risk index. We explored the potential application value of prognostic signatures and LMRS in precise treatment from multiple perspectives.

Results

Through comprehensive analysis, we identified five lipid metabolism-related prognostic signatures (ACADM, ACAT1, ECHS1, HPGD, DGKZ). We developed a risk index LMRS, which was significantly associated with poor prognosis in patients. There was a significant correlation between LMRS and the infiltration levels of multiple immune cells. Patients with high LMRS may be more likely to respond to immunotherapy. The different LMRS groups were suitable for different anticancer drug treatment regimens.

Conclusion

Prognostic signatures and LMRS we developed may be applied to the risk assessment of ccRCC patients, which may have potential guiding significance in the diagnosis and precise treatment of ccRCC patients.

Molecular analysis of primary and metastatic sites in patients with renal cell carcinoma

BACKGROUNDMetastases are the hallmark of lethal cancer, though underlying mechanisms that drive metastatic spread to specific organs remain poorly understood. Renal cell carcinoma (RCC) is known to have distinct sites of metastases, with lung, bone, liver, and lymph nodes being more common than brain, gastrointestinal tract, and endocrine glands. Previous studies have shown varying clinical behavior and prognosis associated with the site of metastatic spread; however, little is known about the molecular underpinnings that contribute to the differential outcomes observed by the site of metastasis.METHODSWe analyzed primary renal tumors and tumors derived from metastatic sites to comprehensively characterize genomic and transcriptomic features of tumor cells as well as to evaluate the tumor microenvironment at both sites.RESULTSWe included a total of 657 tumor samples (340 from the primary site [kidney] and 317 from various sites of metastasis). We show distinct genomic alterations, transcriptomic signatures, and immune and stromal tumor microenvironments across metastatic sites in a large cohort of patients with RCC.CONCLUSIONWe demonstrate significant heterogeneity among primary tumors and metastatic sites and elucidate the complex interplay between tumor cells and the extrinsic tumor microenvironment that is vital for developing effective anticancer therapies.

Radiogenomic analysis based on lipid metabolism-related subset for non-invasive prediction for prognosis of renal clear cell carcinoma

PURPOSE

Multiple lipid metabolism pathways alterations are associated with clear cell renal cell carcinoma (ccRCC) development and aggressiveness. In this study, we aim to develop a novel radiogenomics signature based on lipid metabolism-related genes (LMRGs) that may accurately predict ccRCC patients' survival.

MATERIALS AND METHODS

First, 327 ccRCC were used to screen survival-related LMRGs and construct a gene signature based on The Cancer Genome Atlas (TCGA) database. Then, 182 ccRCC were analyzed to establish radiogenomics signature linking LMRGs signature to radiomic features in The Cancer Imaging Archive (TCIA) database included enhanced CT images and transcriptome sequencing data. Lastly, we validated the prognostic power of the identified radiogenomics signature using these patients of TCIA and the Third Xiangya Hospital.

RESULTS

We identified the LMRGs signature, consisting of 13 genes, which could efficiently discriminate between low-risk and high-risk patients and serve as an independent and reliable predictor of overall survival (OS). Radiogenomics signature, comprised of 9 radiomic features, was created and could accurately predict the expression level of LMRGs signature (low- or high-risk) for patients. The predictive performance of this radiogenomics signature was demonstrated through AUC values of 0.75 and 0.74 for the training and validation sets (at a ratio of 7:3), respectively. Radiogenomics signature was proven to be an independent risk factor for OS by multivariable analysis (HR = 4.98, 95 % CI:1.72-14.43, P = 0.003).

CONCLUSIONS

The LMRGs radiogenomics signature could serve as a novel prognostic predictor.

Understanding Factors that Influence Prognosis and Response to Therapy in Clear Cell Renal Cell Carcinoma

In this review, we highlight and contextualize emerging morphologic prognostic and predictive factors in renal cell carcinoma. We focus on clear cell renal cell carcinoma (ccRCC), the most common histologic subtype. Our understanding of the molecular characterization of ccRCC has dramatically improved in the last decade. Herein, we highlight how these discoveries have laid the foundation for new approaches to prognosis and therapeutic decision-making for patients with ccRCC. We explore the clinical relevance of common mutations, established gene expression signatures, intratumoral heterogeneity, sarcomatoid/rhabdoid morphology and PD-L1 expression, and discuss their impact on predicting response to therapy.

Kidney cancer: Links between hereditary syndromes and sporadic tumorigenesis

Multiple hereditary syndromes predispose to kidney cancer, including Von Hippel-Lindau syndrome, BAP1-Tumor Predisposition Syndrome, Hereditary Papillary Renal Cell Carcinoma, Tuberous Sclerosis Complex, Birt-Hogg-Dubé syndrome, Hereditary Paraganglioma-Pheochromocytoma Syndrome, Fumarate Hydratase Tumor Predisposition Syndrome, and Cowden syndrome. In some cases, mutations in the genes that cause hereditary kidney cancer are tightly linked to similar histologic features in sporadic RCC. For example, clear cell RCC occurs in the hereditary syndrome VHL, and sporadic ccRCC usually has inactivation of the VHL gene. In contrast, mutations in FLCN, the causative gene for Birt-Hogg-Dube syndrome, are rarely found in sporadic RCC. Here, we focus on the genes and pathways that link hereditary and sporadic RCC.

Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing the most detailed somatic mutational landscape to date. We identify new driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for drug repurposing. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The twin observations that higher T-cell infiltration is associated with better outcome and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.

Genomic Profiling and Molecular Characterization of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) treatment has undergone three major paradigm shifts in recent years, first with the introduction of molecular targeted therapies, then with immune checkpoint inhibitors, and, more recently, with immune-based combinations. However, to date, molecular predictors of response to targeted agents have not been identified for ccRCC. The WHO 2022 classification of renal neoplasms introduced the molecularly defined RCC class, which is a first step in the direction of a better molecular profiling of RCC. We reviewed the literature data on known genomic alterations of clinical interest in ccRCC, discussing their prognostic and predictive role. In particular, we explored the role of VHL, mTOR, chromatin modulators, DNA repair genes, cyclin-dependent kinases, and tumor mutation burden. RCC is a tumor whose pivotal genomic alterations have pleiotropic effects, and the interplay of these effects determines the tumor phenotype and its clinical behavior. Therefore, it is difficult to find a single genomic predictive factor, but it is more likely to identify a signature of gene alterations that could impact prognosis and response to specific treatment. To accomplish this task, the interpolation of large amounts of clinical and genomic data is needed. Nevertheless, genomic profiling has the potential to change real-world clinical practice settings.

von-Hippel Lindau and Hypoxia-Inducible Factor at the Center of Renal Cell Carcinoma Biology

The most common form of kidney cancer is clear cell renal cell carcinoma (ccRCC). Biallelic VHL tumor suppressor gene inactivation is the usual initiating event in both hereditary (VHL Disease) and sporadic ccRCCs. The VHL protein, pVHL, earmarks the alpha subunits of the HIF transcription factor for destruction in an oxygen-dependent manner. Deregulation of HIF2 drives ccRCC pathogenesis. Drugs inhibiting the HIF2-responsive growth factor VEGF are now mainstays of ccRCC treatment. A first-in-class allosteric HIF2 inhibitor was recently approved for treating VHL Disease-associated neoplasms and appears active against sporadic ccRCC in early clinical trials.

Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma

PURPOSE

Patients with resected localized clear-cell renal cell carcinoma (ccRCC) remain at variable risk of recurrence. Incorporation of biomarkers may refine risk prediction and inform adjuvant treatment decisions. We explored the role of tumor genomics in this setting, leveraging the largest cohort to date of localized ccRCC tissues subjected to targeted gene sequencing.

EXPERIMENTAL DESIGN

The somatic mutation status of 12 genes was determined in 943 ccRCC cases from a multinational cohort of patients, and associations to outcomes were examined in a Discovery (n = 469) and Validation (n = 474) framework.

RESULTS

Tumors containing a von-Hippel Lindau (VHL) mutation alone were associated with significantly improved outcomes in comparison with tumors containing a VHL plus additional mutations. Within the Discovery cohort, those with VHL+0, VHL+1, VHL+2, and VHL+≥3 tumors had disease-free survival (DFS) rates of 90.8%, 80.1%, 68.2%, and 50.7% respectively, at 5 years. This trend was replicated in the Validation cohort. Notably, these genomically defined groups were independent of tumor mutational burden. Amongst patients eligible for adjuvant therapy, those with a VHL+0 tumor (29%) had a 5-year DFS rate of 79.3% and could, therefore, potentially be spared further treatment. Conversely, patients with VHL+2 and VHL+≥3 tumors (32%) had equivalent DFS rates of 45.6% and 35.3%, respectively, and should be prioritized for adjuvant therapy.

CONCLUSIONS

Genomic characterization of ccRCC identified biologically distinct groups of patients with divergent relapse rates. These groups account for the ∼80% of cases with VHL mutations and could be used to personalize adjuvant treatment discussions with patients as well as inform future adjuvant trial design.

Differential Activation of NRF2 Signaling Pathway in Renal-Cell Carcinoma Caki Cell Lines

Renal-cell carcinoma (RCC) is a heterogeneous disease consisting of several subtypes based on specific genomic profiles and histological and clinical characteristics. The subtype with the highest prevalence is clear-cell RCC (ccRCC), next is papillary RCC (pRCC), and then chromophobe RCC (chRCC). The ccRCC cell lines are further subdivided into prognostic expression-based subtypes ccA or ccB. This heterogeneity necessitates the development, availability, and utilization of cell line models with the correct disease phenotypic characteristics for RCC research. In this study, we focused on characterizing proteomic differences between the Caki-1 and Caki-2 cell lines that are commonly used in ccRCC research. Both cells are primarily defined as human ccRCC cell lines. Caki-1 cell lines are metastatic, harboring wild-type VHL, whereas Caki-2 are considered as the primary ccRCC cell lines expressing wild-type von Hippel–Lindau protein (pVHL). Here, we performed a comprehensive comparative proteomic analysis of Caki-1 and Caki-2 cells using tandem mass-tag reagents together with liquid chromatography mass spectrometry (LC/MS) for the identification and quantitation of proteins in the two cell lines. Differential regulation of a subset of the proteins identified was validated using orthogonal methods including western blot, q-PCR, and immunofluorescence assays. Integrative bioinformatic analysis identifies the activation/inhibition of specific molecular pathways, upstream regulators, and causal networks that are uniquely regulated and associated with the two cell lines and RCC subtypes, and potentially the disease stage. Altogether, we have identified multiple molecular pathways, including NRF2 signaling, which is the most significantly activated pathway in Caki-2 versus Caki-1 cells. Some of the differentially regulated molecules and signaling pathways could serve as potential diagnostic and prognostic biomarkers and therapeutic targets amongst ccRCC subtypes.

The expanding role of BAP1 in clear cell renal cell carcinoma

Mutations drive renal cell carcinoma biology and tumor growth. The BRCA1-associated protein-1 (BAP1) gene is frequently mutated in clear cell renal cell carcinoma (ccRCC) and has emerged as a prognostic and putative predictive biomarker. In this review, we discuss the role of BAP1 as a signature event of a subtype of ccRCC marked by aggressiveness, inflammation, and possibly a heightened response to immunotherapy.

Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects

Renal cancer management is challenging from diagnosis to treatment and follow-up. In cases of small renal masses and cystic lesions the differential diagnosis of benign or malignant tissues has potential pitfalls when imaging or even renal biopsy is applied. The recent artificial intelligence, imaging techniques, and genomics advancements have the ability to help clinicians set the stratification risk, treatment selection, follow-up strategy, and prognosis of the disease. The combination of radiomics features and genomics data has achieved good results but is currently limited by the retrospective design and the small number of patients included in clinical trials. The road ahead for radiogenomics is open to new, well-designed prospective studies, with large cohorts of patients required to validate previously obtained results and enter clinical practice.

Targeting BAP1 with small compound inhibitor for colon cancer treatment

BRCA1-associated protein-1 (BAP1) is a ubiquitin C-terminal hydrolase domain-containing deubiquitinase. The gene encoding BAP1 is mutated in various human cancers, including mesothelioma, uveal melanoma and renal cell carcinoma. BAP1 plays roles in many cancer-related cellular functions, including cell proliferation, cell death, and nuclear processes crucial for genome stability, such as DNA repair and replication. While these findings suggest that BAP1 functions as a tumor suppressor, recent data also suggest that BAP1 might play tumor-promoting roles in certain cancers, such as breast cancer and hematopoietic malignancies. Here, we show that BAP1 is upregulated in colon cancer cells and tissues and that BAP1 depletion reduces colon cancer cell proliferation and tumor growth. BAP1 contributes to colon cancer cell proliferation by accelerating DNA replication and suppressing replication stress and concomitant apoptosis. A recently identified BAP1 inhibitor, TG2-179-1, which seems to covalently bind to the active site of BAP1, exhibits potent cytotoxic activity against colon cancer cells, with half-maximal inhibitory concentrations of less than 10 μM, and inhibits colon tumor growth. TG2-179-1 exerts cytotoxic activity by targeting BAP1, leading to defective replication and increased apoptosis. This work therefore shows that BAP1 acts oncogenically in colon cancer and is a potential therapeutic target for this cancer. Our work also suggests that TG2-179-1 can be developed as a potential therapeutic agent for colon cancer.

BAP1 promotes the repair of UV-induced DNA damage via PARP1-mediated recruitment to damage sites and control of activity and stability

BRCA1-associated protein-1 (BAP1) is a ubiquitin C-terminal hydrolase domain-containing deubiquitinase with tumor suppressor activity. The gene encoding BAP1 is mutated in various human cancers, with particularly high frequency in kidney and skin cancers, and BAP1 is involved in many cancer-related cellular functions, such as DNA repair and genome stability. Although BAP1 stimulates DNA double-strand break repair, whether it functions in nucleotide excision repair (NER) is unknown. Here, we show that BAP1 promotes the repair of ultraviolet (UV)-induced DNA damage via its deubiquitination activity in various cell types, including primary melanocytes. Poly(ADP-ribose) polymerase 1 (PARP1) interacts with and recruits BAP1 to damage sites, with BAP1 recruitment peaking after the DDB2 and XPC damage sensors. BAP1 recruitment also requires histone H2A monoubiquitinated at Lys119, which accumulates at damage sites. PARP1 transiently poly(ADP-ribosyl)ates (PARylates) BAP1 at multiple sites after UV damage and stimulates the deubiquitination activity of BAP1 both intrinsically and via PARylation. PARP1 also promotes BAP1 stability via crosstalk between PARylation and ubiquitination. Many PARylation sites in BAP1 are mutated in various human cancers, among which the glutamic acid (Glu) residue at position 31, with particularly frequent mutation in kidney cancer, plays a critical role in BAP1 stabilization and promotes UV-induced DNA damage repair. Glu31 also participates in reducing the viability of kidney cancer cells. This study therefore reveals that BAP1 functions in the NER pathway and that PARP1 plays a role as a novel factor that regulates BAP1 enzymatic activity, protein stability, and recruitment to damage sites. This activity of BAP1 in NER, along with its cancer cell viability-reducing activity, may account for its tumor suppressor function.

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

BAP1 maintains HIF-dependent interferon beta induction to suppress tumor growth in clear cell renal cell carcinoma

BRCA1-associated protein 1 (BAP1) is a deubiquitinase that is mutated in 10-15% of clear cell renal cell carcinomas (ccRCC). Despite the association between BAP1 loss and poor clinical outcome, the critical tumor suppressor function(s) of BAP1 in ccRCC remains unclear. Previously, we found that hypoxia-inducible factor 2α (HIF2α) and BAP1 activate interferon-stimulated gene factor 3 (ISGF3), a transcription factor activated by type I interferons and a tumor suppressor in ccRCC xenograft models. Here, we aimed to determine the mechanism(s) through which HIF and BAP1 regulate ISGF3. We found that in ccRCC cells, loss of the von Hippel-Lindau tumor suppressor (VHL) activated interferon beta (IFN-β) expression in a HIF2α-dependent manner. IFN-β was required for ISGF3 activation and suppressed the growth of Ren-02 tumors in xenografts. BAP1 enhanced the expression of IFN-β and stimulator of interferon genes (STING), both of which activate ISGF3. Both ISGF3 overexpression and STING agonist treatment increased ISGF3 activity and suppressed BAP1-deficient tumor growth in Ren-02 xenografts. Our results indicate that BAP1 loss reduces type I interferon signaling, and reactivating this pathway may be a novel therapeutic strategy for treating ccRCC.

Exploring synthetic lethal network for the precision treatment of clear cell renal cell carcinoma

The emerging targeted therapies have revolutionized the treatment of advanced clear cell renal cell carcinoma (ccRCC) over the past 15 years. Nevertheless, lack of personalized treatment limits the development of effective clinical guidelines and improvement of patient prognosis. In this study, large-scale genomic profiles from ccRCC cohorts were explored for integrative analysis. A credible method was developed to identify synthetic lethality (SL) pairs and a list of 72 candidate pairs was determined, which might be utilized to selectively eliminate tumors with genetic aberrations using SL partners of specific mutations. Further analysis identified BRD4 and PRKDC as novel medical targets for patients with BAP1 mutations. After mapping these target genes to the comprehensive drug datasets, two agents (BI-2536 and PI-103) were found to have considerable therapeutic potentials in the BAP1 mutant tumors. Overall, our findings provided insight into the overview of ccRCC mutation patterns and offered novel opportunities for improving individualized cancer treatment.

High VHL Expression Reverses Warburg Phenotype and Enhances Immunogenicity in Kidney Tumor Cells

Clear cell renal cell carcinoma (ccRCC) is a frequently occurring renal cancer. The Von Hippel-Lindau disease tumor suppressor VHL, a known tumor suppressor gene, is frequently mutated in about 50% of patients with ccRCC. However, it is unclear whether VHL influences the progression of ccRCC tumors expressing wild-type VHL. In the present study, we found that higher expression of VHL was correlated with the better disease-free survival (DFS) in ccRCC patients using The Cancer Genome Atlas (TCGA) datasets. We revealed that VHL overexpression in ccRCC cells inhibited epithelial-mesenchymal transition (EMT), sterol regulatory element-binding protein 1 (SREBP1)-regulated triglyceride synthesis, and cell proliferation. Proteomic analysis provided us a global view that VHL regulated four biological processes, including metabolism, immune regulation, apoptosis, and cell movement. Importantly, we found that VHL overexpression led to up-regulated expression of proteins associated with antigen processing and interferon-responsive proteins, thus rendering ccRCC cells more sensitive to interferon treatment. We defined an interferon-responsive signature (IRS) composed of ten interferon-responsive proteins, whose mRNA expression levels were positively correlated with DFS in ccRCC patients. Taken together, our results propose that the subset of ccRCC patients with high VHL expression benefit from immunotherapy.

Clinical Benefit of Niraparib to TKI/mTORi-Resistance Metastatic ccRCC With BAP1-Frame Shift Mutation: Case Report and Literature Review

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer. The top four mutant genes affecting the occurrence and progression of ccRCC are VHL, PBRM1, BAP1, and SETD2, respectively. Tyrosine kinase/mammalian target of rapamycin inhibitors (TKI/mTORis) with or without immunotherapy are the standard and effective therapy to metastatic ccRCC. Once TKI/mTORis fail to ccRCC, there is still a lack of other effective therapies. In this study, we reported a case in which a metastatic ccRCC patient (T2aN1M1) presented resistance after a 28-month treatment by sorafenib–axitinib–everolimus (TKI-TKI-mTORi). Subsequently, a frame shift pathogenic mutation, c.799_800del (p.Q267fs) in the exon10 of BAP1 in ccRCC, was revealed by targeted sequencing. Oral administration of nilapanib (PARP inhibitor) was further given, which may provide a new therapy for TKI/mTORi-resistance metastatic ccRCC. Fortunately, a partial response has been achieved and lasted for 5 months. Since the frequency of BAP1 mutations in ccRCC patients was approximately 10%–20%, as reported previously, we also tried to explore the potential mechanisms benefitting from the nilapanib. Moreover, the literature concerning BAP1 mutation and associated cancers including ccRCC is reviewed.

Evaluation of Annexins Family as Potential Biomarker for Predicting Progression and Prognosis in Clear Renal Cell Carcinoma

Background

Annexins family (ANXAs), as a Ca2+-dependent phospholipid-binding protein superfamily, participates in a wide variety of biological activities and has been reported to be dysregulated in numerous types of human cancers. Evidence from cell lines and human tissues indicates that ANAXs are involved in kidney clear renal cell carcinoma (KIRC) tumorigenesis. However, their prognostic value and expression pattern associated with KIRC remain to be elucidated.

Methods

We visited public databases, including ONCOMINE, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier plotter, cBioPortal, and GeneMANIA, to conduct comprehensive bioinformatics analysis and tried to detect basic relationships between each Annexins family member and KIRC.

Results

We found that the expression level of ANXA1/2/4/5/6/7/8/13 in clear renal cell carcinoma tissue was higher than that in the kidney tissue, while the expression level of ANXA3/9/11 in the former was lower than that in the latter. The expression level of ANXA7/8/13 is related to the stage of the tumour. Survival analysis using the Kaplan-Meier plotter database showed that a high transcription level of ANXA2/5/8/10 is related to a low overall survival rate (OS) in predicting KIRC patients. In contrast, high ANXA3/4/7/9/11/13 levels are associated with a high OS in these patients.

Conclusions

Our study implies that ANXA4/8/13 are potential targets of precision therapy for patients with KIRC and that ANXA2/5/8/10 are new biomarkers for the prognosis of KIRC.

Panel Informativity Optimizer: An R Package to Improve Cancer Next-Generation Sequencing Panel Informativity

Mutation detection by next-generation sequencing is routinely used for cancer diagnosis. Selecting an optimal set of genes for a given cancer is not trivial as it has to optimize informativity (ie, the number of patients with at least one mutation in the panel), while minimizing panel length to reduce sequencing costs and increase sensitivity. We propose herein Panel Informativity Optimizer (PIO), an open-source software developed as an R package with a user-friendly graphical interface to help optimize cancer next-generation sequencing panel informativity. Using patient-level mutational data from either private data sets or preloaded data set of 91 independent cohorts from 31 different cancer types, PIO selects an optimal set of genomic intervals to maximize informativity and panel size in a given cancer type. Different options are offered, such as the definition of genomic intervals at the gene or exon level and the use of optimization strategy at the patient or patient per kilobase level. PIO can also propose an optimal set of genomic intervals to increase informativity of custom panels. A panel tester function is also available for panel benchmarking. Using public databases, as well as data from real-life settings, we demonstrate that PIO allows panel size reduction of up to 1000 kb, and accurately predicts the performance of custom or commercial panels.

Hypoxia classifier for transcriptome datasets

Molecular gene signatures are useful tools to characterize the physiological state of cell populations, but most have developed under a narrow range of conditions and cell types and are often restricted to a set of gene identities. Focusing on the transcriptional response to hypoxia, we aimed to generate widely applicable classifiers sourced from the results of a meta-analysis of 69 differential expression datasets which included 425 individual RNA-seq experiments from 33 different human cell types exposed to different degrees of hypoxia (0.1-5%[Formula: see text]) for 2-48 h. The resulting decision trees include both gene identities and quantitative boundaries, allowing for easy classification of individual samples without control or normoxic reference. Each tree is composed of 3-5 genes mostly drawn from a small set of just 8 genes (EGLN1, MIR210HG, NDRG1, ANKRD37, TCAF2, PFKFB3, BHLHE40, and MAFF). In spite of their simplicity, these classifiers achieve over 95% accuracy in cross validation and over 80% accuracy when applied to additional challenging datasets. Our results indicate that the classifiers are able to identify hypoxic tumor samples from bulk RNAseq and hypoxic regions within tumor from spatially resolved transcriptomics datasets. Moreover, application of the classifiers to histological sections from normal tissues suggest the presence of a hypoxic gene expression pattern in the kidney cortex not observed in other normoxic organs. Finally, tree classifiers described herein outperform traditional hypoxic gene signatures when compared against a wide range of datasets. This work describes a set of hypoxic gene signatures, structured as simple decision tress, that identify hypoxic samples and regions with high accuracy and can be applied to a broad variety of gene expression datasets and formats.

BAP1-Related ceRNA (NEAT1/miR-10a-5p/SERPINE1) Promotes Proliferation and Migration of Kidney Cancer Cells

Background

BAP1 is an important tumor suppressor involved in various biological processes and is commonly lost or inactivated in clear-cell renal cell carcinoma (ccRCC). However, the role of the BAP1-deficient tumor competing endogenous RNA (ceRNA) network involved in ccRCC remains unclear. Thus, this study aims to investigate the prognostic BAP1-related ceRNA in ccRCC.

Methods

Raw data was obtained from the TCGA and the differentially expressed genes were screened to establish a BAP1-related ceRNA network. Subsequently, the role of the ceRNA axis was validated using phenotypic experiments. Dual-luciferase reporter assays and fluorescence in situ hybridization (FISH) assays were used to confirm the ceRNA network.

Results

Nuclear enriched abundant transcript 1 (NEAT1) expression was significantly increased in kidney cancer cell lines. NEAT1 knockdown significantly inhibited cell proliferation and migration, which could be reversed by miR-10a-5p inhibitor. Dual-luciferase reporter assay confirmed miR-10a-5p as a common target of NEAT1 and Serine protease inhibitor family E member 1 (SERPINE1). FISH assays revealed the co-localization of NEAT1 and miR-10a-5p in the cytoplasm. Additionally, the methylation level of SERPINE1 in ccRCC was significantly lower than that in normal tissues. Furthermore, SERPINE1 expression was positively correlated with multiple immune cell infiltration levels.

Conclusions

In BAP1-deficient ccRCC, NEAT1 competitively binds to miR-10a-5p, indirectly upregulating SERPINE1 expression to promote kidney cancer cell proliferation. Furthermore, NEAT1/miR-10a-5p/SERPINE1 were found to be independent prognostic factors of ccRCC.

Sensitivity of VHL mutant kidney cancers to HIF2 inhibitors does not require an intact p53 pathway

VHL tumor suppressor gene inactivation is a hallmark of clear cell renal cell carcinoma (ccRCC), the most common form of kidney cancer, and promotes tumor growth by stabilizing the hypoxia-inducible factor 2 (HIF2) transcription factor. HIF2 inhibitors appear to be helpful for some, but not all, ccRCC patients in clinical trials. Previous preclinical and clinical data suggested that only ccRCCs that can activate the p53 tumor suppressor in response to DNA damage would respond to HIF2 inhibitors. Here, we show that an intact p53 pathway is neither necessary nor sufficient for the sensitivity of ccRCCs to HIF2 inhibitors, suggesting that it would be premature to use p53 status to determine which ccRCC patients should be treated with a HIF2 inhibitor.

Inactivation of the VHL tumor suppressor gene is the signature initiating event in clear cell renal cell carcinoma (ccRCC), which is the most common form of kidney cancer. The VHL tumor suppressor protein marks hypoxia-inducible factor 1 (HIF1) and HIF2 for proteasomal degradation when oxygen is present. The inappropriate accumulation of HIF2 drives tumor formation by VHL tumor suppressor protein (pVHL)–defective ccRCC. Belzutifan, a first-in-class allosteric HIF2 inhibitor, has advanced to phase 3 testing for advanced ccRCC and is approved for ccRCCs arising in patients with VHL disease, which is caused by germline VHL mutations. HIF2 can suppress p53 function in some settings and preliminary data suggested that an intact p53 pathway, as measured by activation in response to DNA damage, was necessary for HIF2 dependence. Here, we correlated HIF2 dependence and p53 status across a broader collection of ccRCC cell lines. We also genetically manipulated p53 function in ccRCC lines that were or were not previously HIF2-dependent and then assessed their subsequent sensitivity to HIF2 ablation using CRISPR-Cas9 or the HIF2 inhibitor PT2399, which is closely related to belzutifan. From these studies, we conclude that p53 status does not dictate HIF2 dependence, at least in preclinical models, and thus is unlikely to be a useful biomarker for predicting which ccRCC patients will respond to HIF2 inhibitors.

Renal Neoplasms in Young Adults

Renal cell carcinoma (RCC) is usually diagnosed in older adults (the median age of diagnosis is 64 years). Although less common in patients younger than 45 years, RCCs in young adults differ in clinical manifestation, pathologic diagnosis, and prognosis. RCCs in young adults are typically smaller, are more organ confined, and manifest at lower stages of disease. The proportion of clear cell RCC is lower in young adults, while the prevalence of familial renal neoplastic syndromes is much higher, and genetic testing is routinely recommended. In such syndromic manifestations, benign-appearing renal cysts can harbor malignancy. Radiologists need to be familiar with the differences of RCCs in young adults and apply an altered approach to diagnosis, treatment, and surveillance. For sporadic renal neoplasms, biopsy and active surveillance are less often used in young adults than in older adults. RCCs in young adults are overall associated with better disease-specific survival after surgical treatment, and minimally invasive nephron-sparing treatment options are preferred. However, surveillance schedules, need for biopsy, decision for an initial period of active surveillance, type of surgery (enucleation or wide-margin partial nephrectomy), and utilization of ablative therapy depend on the presence and type of underlying familial renal neoplastic syndrome. In this pictorial review, syndromic, nonsyndromic, and newer RCC entities that are common in young adults are presented. Their associated unique epidemiology, characteristic imaging and pathologic traits, and key aspects of surveillance and management of renal neoplasms in young adults are discussed. The vital role of the informed radiologist in the multidisciplinary management of RCCs in young adults is highlighted. Online supplemental material is available for this article. ^©RSNA, 2022.

Data-driven design of targeted gene panels for estimating immunotherapy biomarkers

Tumour mutation burden and other exome-wide biomarkers are used to determine which patients will benefit from immunotherapy. However, the cost of whole exome sequencing limits the widespread use of such biomarkers. Here, we introduce a data-driven framework for the design of targeted gene panels for estimating a broad class of biomarkers including tumour mutation burden and tumour indel burden. Our first goal is to develop a generative model for the profile of mutation across the exome, which allows for gene- and variant type-dependent mutation rates. Based on this model, we then propose a procedure for constructing biomarker estimators. Our approach allows the practitioner to select a targeted gene panel of prespecified size and construct an estimator that only depends on the selected genes. Alternatively, our method may be applied to make predictions based on an existing gene panel, or to augment a gene panel to a given size. We demonstrate the excellent performance of our proposal using data from three non small-cell lung cancer studies, as well as data from six other cancer types.

TET2 suppresses VHL deficiency-driven clear cell renal cell carcinoma by inhibiting HIF signaling

Inactivating mutations of von Hippel-Lindau (VHL) are highly prevalent in clear cell renal cell carcinoma (ccRCC). Improved understanding of the vulnerabilities of VHL-deficient ccRCC could lead to improved treatment strategies. The activity of DNA dioxygenase TET2 is significantly reduced in multiple cancers by different mechanisms, but its role in ccRCC progression remains unclear. Here, we report that increased expression of TET2, but not TET1 and TET3, is negatively associated with tumor metastasis and advanced tumor stage and positively associated with good prognosis uniquely in ccRCC among all 33 types of cancer in the TCGA datasets. TET2 restrained glycolysis and pentose phosphate pathway metabolism in a VHL deficiency-dependent manner, thereby suppressing ccRCC progression. Notably, TET2 and VHL mutations tended to co-occur in ccRCC, providing genetic evidence that they cooperate to inhibit the progression of ccRCC. Mechanistically, TET2 was recruited by transcription factor HNF4α to activate FBP1 expression, which antagonized the function of HIF1/2α in metabolic reprogramming to impede ccRCC growth. Stimulating the TET2-FBP1 axis with vitamin C repressed the growth of VHL-deficient ccRCC with wild-type TET2 and increased the sensitivity to glycolysis inhibitors. Moreover, combined expression levels of the HNF4α-TET2-FBP1 axis served as a biomarker of prognosis in ccRCC patients. This study reveals a unique function of TET2 in the suppression of tumor metabolism and HIF signaling, and it also provides therapeutic targets, potential drugs, and prognostic markers for the management of ccRCC.

BRCA1-Associated Protein 1 (BAP-1) as a Prognostic and Predictive Biomarker in Clear Cell Renal Cell Carcinoma: A Systematic Review

BACKGROUND: The gene that encodes BRCA1-associated protein 1 (BAP1) has been reported to be dysregulated in several human cancers such as uveal melanoma, malignant pleural mesothelioma, hepatocellular carcinoma, thymic epithelial tumors, and clear-cell renal cell carcinoma (ccRCC). The gene is located on the human chromosome 3p21.3, encoding a deubiquitinase and acts as a classic two-hit tumor suppressor gene. BAP1 predominantly resides in the nucleus, where it interacts with several chromatin-associated factors, as well as regulates calcium signaling in the cytoplasm. As newer therapies continue to evolve for the management of RCC, it is important to understand the role of BAP1 mutation as a prognostic and predictive biomarker. OBJECTIVE: We aimed to systematically evaluate the role of BAP1 mutations in patients with RCC in terms of its impact on prognosis and its role as a predictive biomarker. METHODS: Following PRISMA guidelines, we performed a systematic literature search using PubMed and Embase through March 2021. Titles and abstracts were screened to identify articles for full-text and then a descriptive review was performed. RESULTS: A total of 490 articles were initially identified. Ultimately 71 articles that met our inclusion criteria published between 2012–2021 were included in the analysis. Data were extracted and organized to reflect the role of BAP1 alterations as a marker of prognosis as well as a marker of response to treatments, such as mTOR inhibitors, VEGF tyrosine kinase inhibitors, and immune checkpoint inhibitors. CONCLUSIONS: Alterations in BAP1 appear to be uniformly associated with poor prognosis in patients with RCC. Knowledge gaps remain with regard to the predictive relevance of BAP1 alterations, especially in the context of immunotherapy. Prospective studies are required to more precisely ascertain the predictive value of BAP1 alterations in RCC.

ParsVNN: parsimony visible neural networks for uncovering cancer-specific and drug-sensitive genes and pathways

Prediction of cancer-specific drug responses as well as identification of the corresponding drug-sensitive genes and pathways remains a major biological and clinical challenge. Deep learning models hold immense promise for better drug response predictions, but most of them cannot provide biological and clinical interpretability. Visible neural network (VNN) models have emerged to solve the problem by giving neurons biological meanings and directly casting biological networks into the models. However, the biological networks used in VNNs are often redundant and contain components that are irrelevant to the downstream predictions. Therefore, the VNNs using these redundant biological networks are overparameterized, which significantly limits VNNs' predictive and explanatory power. To overcome the problem, we treat the edges and nodes in biological networks used in VNNs as features and develop a sparse learning framework ParsVNN to learn parsimony VNNs with only edges and nodes that contribute the most to the prediction task. We applied ParsVNN to build cancer-specific VNN models to predict drug response for five different cancer types. We demonstrated that the parsimony VNNs built by ParsVNN are superior to other state-of-the-art methods in terms of prediction performance and identification of cancer driver genes. Furthermore, we found that the pathways selected by ParsVNN have great potential to predict clinical outcomes as well as recommend synergistic drug combinations.

Exploration of Alternative Splicing (AS) Events in MDV-Infected Chicken Spleens

Marek’s disease (MD) was an immunosuppression disease induced by Marek’s disease virus (MDV). MD caused huge economic loss to the global poultry industry, but it also provided an ideal model for studying diseases induced by the oncogenic virus. Alternative splicing (AS) simultaneously produced different isoform transcripts, which are involved in various diseases and individual development. To investigate AS events in MD, RNA-Seq was performed in tumorous spleens (TS), spleens from the survivors (SS) without any lesion after MDV infection, and non-infected chicken spleens (NS). In this study, 32,703 and 25,217 AS events were identified in TS and SS groups with NS group as the control group, and 1198, 1204, and 348 differently expressed (DE) AS events (p-value < 0.05 and FDR < 0.05) were identified in TS vs. NS, TS vs. SS, SS vs. NS, respectively. Additionally, Function enrichment analysis showed that ubiquitin-mediated proteolysis, p53 signaling pathway, and phosphatidylinositol signaling system were significantly enriched (p-value < 0.05). Small structural variations including SNP and indel were analyzed based on RNA-Seq data, and it showed that the TS group possessed more variants on the splice site region than those in SS and NS groups, which might cause more AS events in the TS group. Combined with previous circRNA data, we found that 287 genes could produce both circular and linear RNAs, which suggested these genes were more active in MD lymphoma transformation. This study has expanded the understanding of the MDV infection process and provided new insights for further analysis of resistance/susceptibility mechanisms.

Prognostic Significance of Alternative Splicing Genes in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Background

Alternative splicing (AS) acts on many tumors and its relationship with cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) needs to be researched.

Methods

RNA sequencing data and clinical information of CESC cohorts were obtained from the Cancer Genome Atlas (TCGA) and SpliceSeq was used to analyze the splicing profile of mRNA in CESC. UpSetR displayed the intersections among AS events and univariate analysis chose survival-associated AS and splicing factor (SF) genes. Functional analysis was operated on Enrichr, STRING database and MCODE analysis were used to evaluate protein-protein interaction (PPI) information. LASSO and multivariate analysis constructed prognostic model and risk analysis of tumor infiltrating immune cells was also conducted.

Results

A total of 402 AS-generated genes were found to be associated with CESC prognosis. Functional analysis showed that Golgi to lysosome transport was enriched. PPI network suggested that UBA52 was most functional. Dendritic cells activated, dendritic cells resting, macrophages M0, mast cells resting, T cells CD4 memory activated and T cells CD8 were most correlative with the risk score.

Conclusion

SFs and AS events can directly or indirectly affect the prognosis of CESC patients and this study identified SNRPA and CELF2 as two CESC-engaged SFs.

H3K36 trimethylation-mediated biological functions in cancer

Histone modification is an important form of epigenetic regulation. Thereinto, histone methylation is a critical determination of chromatin states, participating in multiple cellular processes. As a conserved histone methylation mark, histone 3 lysine 36 trimethylation (H3K36me3) can mediate multiple transcriptional-related events, such as the regulation of transcriptional activity, transcription elongation, pre-mRNA alternative splicing, and RNA m⁶A methylation. Additionally, H3K36me3 also contributes to DNA damage repair. Given the crucial function of H3K36me3 in genome regulation, the roles of H3K36me3 and its sole methyltransferase SETD2 in pathogenesis, especially malignancies, have been emphasized in many studies, and it is conceivable that disruption of histone methylation regulatory network composed of "writer", "eraser", "reader", and the mutation of H3K36me3 codes have the capacity of powerfully modulating cancer initiation and development. Here we review H3K36me3-mediated biological processes and summarize the latest findings regarding its role in cancers. We highlight the significance of epigenetic combination therapies in cancers.

Genome-wide analysis of DNA methylation identifies the apoptosis-related gene UQCRH as a tumor suppressor in renal cancer

DNA hypermethylation is frequently observed in clear cell renal cell carcinoma (ccRCC) and correlates with poor clinical outcomes. However, the detailed function of DNA hypermethylation in ccRCC has not been fully uncovered. Here, we show the role of DNA methylation in ccRCC progression through the identification of a target(s) of DNA methyltransferases (DNMT). Our preclinical model of ccRCC using the serial orthotopic inoculation model showed the upregulation of DNMT3B in advanced ccRCC. Pretreatment of advanced ccRCC cells with 5-aza-deoxycytidine, a DNMT inhibitor, attenuated the formation of primary tumors through the induction of apoptosis. DNA methylated sites were analyzed genome-wide using methylation array in reference to RNA-sequencing data. The gene encoding ubiquinol cytochrome c reductase hinge protein (UQCRH), one of the components of mitochondrial complex III, was extracted as a methylation target in advanced ccRCC. Immunohistochemical analysis revealed that the expression of UQCRH in human ccRCC tissues was lower than normal adjacent tissues. Silencing of UQCRH attenuated the cytochrome c release in response to apoptotic stimuli and resulted in enhancement of primary tumor formation in vivo, implying the tumor-suppressive role of UQCRH. Moreover, 5-aza-deoxycytidine enhanced the therapeutic efficiency of mammalian target of rapamycin inhibitor everolimus in vivo. These findings suggested that the DNMT3B-induced methylation of UQCRH may contribute to renal cancer progression and implicated clinical significance of DNMT inhibitor as a therapeutic option for ccRCC.

BAP1-inactivated melanocytic tumors show prominent centrosome amplification and associated loss of primary cilia

BACKGROUND

BRCA1-associated protein (BAP1) is a tumor suppressor whose loss is associated with various malignancies. The primary cilium is an organelle involved in signal transduction and cell cycle progression. Primary cilia have been shown to be absent in melanoma but retained to some extent in melanocytic nevi, and the severity of dysplasia influences the degree of cilia loss. Additionally, studies have revealed roles for BAP1 in centrosome and mitotic spindle formation. Because the primary cilium is nucleated on the mother centriole, we examined the connection between the presence of primary cilia and the formation of centrosomes in BAP1-inactivated melanocytic tumors (BIMTs).

METHODS

We evaluated the cilia and centrosomes in 11 BIMTs and five conventional melanocytic nevi using immunofluorescence staining of acetylated alpha-tubulin and gamma-tubulin.

RESULTS

We found that, compared to nevi, BIMTs show loss of primary cilia and amplification of centrosomes. Occasional nevi also showed increased centrioles; however, these foci of amplification were more likely to be ciliated than those in BIMTs.

CONCLUSIONS

Although centrosome amplification does not absolutely correlate with loss of primary cilia in melanocytic neoplasms, absence of BAP1 exacerbates the phenotype. Moreover, aberrant centrosome and cilia formation are likely critical in the pathogenesis of other BAP1-inactivated tumors.

Potential role for the tumor suppressor CYLD in brain and notochord development

Background

The cylindromatosis (CYLD) tumor suppressor is a microtubule‐associated deubiquitinase that plays a critical role in the regulation of cell signaling and contributes to a variety of physiological and pathological processes. However, the functions of CYLD in zebrafish are less well known, particularly with regard to their development and physiology. In this context, we investigated the loss of function of CYLD in zebrafish via transcription activator‐like effector nuclease (TALEN)‐based gene deletion.

Methods

Semi‐quantitative RT‐PCR was used to quantify CYLD mRNA expression in zebrafish embryos at various developmental stages. We also performed whole‐mount in situ hybridization to further assess the dynamic expression and distribution of CYLD in the entire zebrafish embryos at different stages. In addition, we deleted CYLD in zebrafish with TALENs to investigate its potential impact on embryonic development.

Results

The expression of CYLD mRNA varied during early embryonic development. The CYLD mRNA localized to the brain and notochord of developing zebrafish embryos. Homozygous deletion of CYLD resulted in embryonic death before 8 h post‐fertilization.

Conclusions

CYLD appears to play an important role in central nervous system development in zebrafish. Although severe embryonic death restricted analysis of homozygous mutants, further research into the role of CYLD in central nervous system development is warranted.

Ubiquitin Modification Patterns of Clear Cell Renal Cell Carcinoma and the Ubiquitin Score to Aid Immunotherapy and Targeted Therapy

Ubiquitin modification is the most common protein post-translational modification (PTM) process in organisms, and 1332 ubiquitin regulators have been identified in humans. Ubiquitin regulators, especially E3 ligases and deubiquitinases, are widely involved in immune processes. This study aims to explore the ubiquitin modification features of clear cell renal cell carcinoma (ccRCC) and to elucidate the role of such ubiquitin modifications in shaping anti-tumor immunity and individual benefits from immune checkpoint blockade (ICB). A comprehensive analysis was performed in the TCGA cohort (n = 530) and GEO cohort (n = 682). RNA sequencing data of 758 differentially expressed regulators, which was validated by the proteomics data, was used for k-means unsupervised consensus clustering and three ubiquitin patterns of ccRCC were identified. Then, we focused on the ubiquitin modification and tumor progression signatures, immune infiltration characteristics, and prognostic value. The three patterns with different ubiquitin modification signatures correspond to “immune desert phenotype,” “immune resistance phenotype,” and “immune-inflammatory phenotype,” respectively. To facilitate clinical application, we constructed a ubiquitin score to evaluate individual patients’ ubiquitination outcome, and it was demonstrated to be an independent risk factor for overall survival (OS) in multivariate Cox analysis. It was found that the high score group was correlated to higher immune cells infiltrating level and PD-1/PD-L1/CTLA-4 expression. More importantly, we found that the high score group was predicted to be sensitive to anti-PD-1 treatment, while the low-score group showed lower predicted IC50 values in treatment with Pazopanib and Axitinib. In summary, this study elucidated the potential link between ubiquitin modification and immune infiltration landscape of ccRCC for the first time and provided a new assessment protocol for the precise selection of treatment strategies for patients with advanced ccRCC.

Improved cancer biomarkers identification using network-constrained infinite latent feature selection

Identifying biomarkers that are associated with different types of cancer is an important goal in the field of bioinformatics. Different researcher groups have analyzed the expression profiles of many genes and found some certain genetic patterns that can promote the improvement of targeted therapies, but the significance of some genes is still ambiguous. More reliable and effective biomarkers identification methods are then needed to detect candidate cancer-related genes. In this paper, we proposed a novel method that combines the infinite latent feature selection (ILFS) method with the functional interaction (FIs) network to rank the biomarkers. We applied the proposed method to the expression data of five cancer types. The experiments indicated that our network-constrained ILFS (NCILFS) provides an improved prediction of the diagnosis of the samples and locates many more known oncogenes than the original ILFS and some other existing methods. We also performed functional enrichment analysis by inspecting the over-represented gene ontology (GO) biological process (BP) terms and applying the gene set enrichment analysis (GSEA) method on selected biomarkers for each feature selection method. The enrichments analysis reports show that our network-constraint ILFS can produce more biologically significant gene sets than other methods. The results suggest that network-constrained ILFS can identify cancer-related genes with a higher discriminative power and biological significance.

Oncogenic mechanisms in renal insufficiency

The prevalence of both cancer and end-stage renal disease is increasing. In addition, medical advances have meant increased survival rates for both diseases. Many chemotherapeutics are renally excreted, and conversely, renal insufficiency promotes a pro-neoplastic state, including genitourinary and other cancers. Dialysis prolongs life while increasing cancer risk. Proposed oncogenic mechanisms include immune dysfunction, chronic inflammation, changes in gut microbiota and stimulation of the renin-angiotensin system. This review summarizes current concepts in the relationship between cancer and renal insufficiency.

Genomic Analysis Reveals Novel Specific Metastatic Mutations in Chinese Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for more than 75% of renal cell carcinoma. Nearly 25% of ccRCC patients were diagnosed with metastasis. Though the genomic profile of ccRCC has been widely studied, the difference between localized and metastatic ccRCC was not clarified. Primary tumor samples and matched whole blood were collected from 106 sporadic patients diagnosed with renal clear cell carcinoma at Qilu Hospital of Shandong University from January 2017 to November 2019, and 17 of them were diagnosed with metastasis. A hybridization capture-based next-generation sequencing of 618 cancer-related genes was performed to investigate the somatic and germline variants, tumor mutation burden (TMB), and microsatellite instability (MSI). Five genes with significantly different prevalence were identified in the metastatic group, especially TOP1 (17.65% vs. 0%) and SNCAIP (17.65% vs. 0%). The altered frequency of PBRM1 (0% vs. 27%) and BAP1 (24% vs. 10%) differed between the metastatic and nonmetastatic groups, which may relate to the prognosis. Of these 106 patients, 42 patients (39.62%) had at least one alteration in DNA damage repair (DDR) genes, including 58.82% of metastatic ccRCC patients and 35.96% of ccRCC patients without metastasis. Ten pathogenic or likely pathogenic (P/LP) variants were identified in 11 sporadic clear cell renal cell carcinoma patients (10.38%), including rarely reported ATM (n=1), MUTYH (n=1), NBN (n=1), RAD51D (n=1), and BRCA2 (n=1). No significant difference in the ratio of P/LP variant carriers or TMB was identified between the metastatic and nonmetastatic groups. We found a unique genomic feature of Chinese metastatic ccRCC patients with a higher prevalence of alterations in DDR, TOP1, and SNCAIP. Further investigated studies and drug development are needed in the future.

Genetic Alterations in Renal Cancers: Identification of The Mechanisms Underlying Cancer Initiation and Progression and of Therapeutic Targets

Renal cell cancer (RCC) involves three most recurrent sporadic types: clear-cell RCC (70-75%, CCRCC), papillary RCCC (10-15%, PRCC), and chromophobe RCC (5%, CHRCC). Hereditary cases account for about 5% of all cases of RCC and are caused by germline pathogenic variants. Herein, we review how a better understanding of the molecular biology of RCCs has driven the inception of new diagnostic and therapeutic approaches. Genomic research has identified relevant genetic alterations associated with each RCC subtype. Molecular studies have clearly shown that CCRCC is universally initiated by Von Hippel Lindau (VHL) gene dysregulation, followed by different types of additional genetic events involving epigenetic regulatory genes, dictating disease progression, aggressiveness, and differential response to treatments. The understanding of the molecular mechanisms that underlie the development and progression of RCC has considerably expanded treatment options; genomic data might guide treatment options by enabling patients to be matched with therapeutics that specifically target the genetic alterations present in their tumors. These new targeted treatments have led to a moderate improvement of the survival of metastatic RCC patients. Ongoing studies based on the combination of immunotherapeutic agents (immune check inhibitors) with VEGF inhibitors are expected to further improve the survival of these patients.

Radiomics and Artificial Intelligence for Renal Mass Characterization

Radiomics allows for high throughput extraction of quantitative data from images. This is an area of active research as groups try to capture and quantify imaging parameters and convert these into descriptive phenotypes of organs or tumors. Texture analysis is one radiomics tool that extracts information about heterogeneity within a given region of interest. This is used with or without associated machine learning classifiers or a deep learning approach is applied to similar types of data. These tools have shown utility in characterizing renal masses, renal cell carcinoma, and assessing response to targeted therapeutic agents in metastatic renal cell carcinoma.

BAP1 promotes stalled fork restart and cell survival via INO80 in response to replication stress

The recovery from replication stress by restarting stalled forks to continue DNA synthesis is crucial for maintaining genome stability and thereby preventing diseases such as cancer. We previously showed that BRCA1-associated protein 1 (BAP1), a nuclear deubiquitinase with tumor suppressor activity, promotes replication fork progression by stabilizing the INO80 chromatin remodeler via deubiquitination and recruiting it to replication forks during normal DNA synthesis. However, whether BAP1 functions in DNA replication under stress conditions is unknown. Here, we show that BAP1 depletion reduces S-phase progression and DNA synthesis after treatment with hydroxyurea (HU). BAP1-depleted cells exhibit a defect in the restart of HU-induced stalled replication forks, which is recovered by the ectopic expression of INO80. Both BAP1 and INO80 bind chromatin at replication forks upon HU treatment. BAP1 depletion abrogates the binding of INO80 to replication forks and increases the formation of RAD51 foci following HU treatment. BAP1-depleted cells show hypersensitivity to HU treatment, which is rescued by INO80 expression. These results suggest that BAP1 promotes the restart of stress-induced stalled replication forks by recruiting INO80 to the stalled forks. This function of BAP1 in replication stress recovery may contribute to its ability to suppress genome instability and cancer development.

KDM5C Represses FASN-Mediated Lipid Metabolism to Exert Tumor Suppressor Activity in Intrahepatic Cholangiocarcinoma

Background: KDM5C is a histone H3K4-specific demethylase, which has multiple biological functions during development and disease. However, the role of KDM5C in intrahepatic cholangiocarcinoma (ICC) remains unknown. Methods: Expression levels of KDM5C in ICC patients were determined by qRT-PCR, western blotting and immunohistochemical assay. The functions of KDM5C in cell proliferation and invasion were determined in human ICC cells and mouse xenograft model using KDM5C overexpression and knockdown strategies in vivo. RNA-seq analysis was applied to investigate the transcriptional program of KDM5C. In addition, ChIP-qPCR was used to determine the regulation of FASN by KDM5C. Results: Here, we show that KDM5C was downregulated in human ICC, where its diminished expression was associated with poor prognosis. ICC cell proliferation and invasion were inhibited by KDM5C overexpression. Moreover, KDM5C suppressed ICC proliferation and metastasis in vivo. RNA-sequencing showed that KDM5C inhibits key signal pathways of cell proliferation, cell invasion and fatty acid metabolism. ChIP-qPCR revealed that overexpression of KDM5C led to the reduction of H3K4me3 on the promoter and the corresponding downregulation of the expression of FASN, which represents the major target gene of KDM5C to mediate the proliferation and invasion of ICC cells. Conclusions: Our results revealed the role of KDM5C as a novel tumor suppressor in ICC largely by repressing FASN-mediated lipid acid metabolism and thus KDM5C may contribute to the pathogenesis of ICC.

Genomic profiling in renal cell carcinoma

The treatment landscape of metastatic renal cell carcinoma (RCC) has been revolutionized over the past two decades, bringing forth an era in which more than a dozen therapeutic agents are now available to treat patients. As a consequence, personalized care has become a critical part of developing effective treatment guidelines and improving patient outcomes. One of the most important emerging aspects of precision medicine in cancer is matching patients and treatments based on the genomic characteristics of an individual and their tumour. Despite the lack of a single genomic predictor of treatment response or prognostication feature in RCC, emerging research suggests that the identification of such markers remains promising. Mutations in VHL and alterations in its downstream pathways are the mainstay of RCC development and progression. However, the predictive value of VHL mutations has been questioned. Further research has examined mutations in genes involved in chromosome remodelling (for example, PBRM1, BAP1 and SETD2), DNA methylation and DNA damage repair, all of which have been associated with clinical outcomes. Here, we provide a comprehensive overview of genomic evidence in the context of RCC and its potential predictive and prognostic value.